2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)最新文献
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00137
Shoufeng Wang, Fan Li, Hao Ni, Lexi Xu, Meifang Jing, Junyi Yu, Xidong Wang
Rush hour network capacity enhancement is one of the most hard-to-solve problems in the field of network optimization. With the bust of data traffic requirement in cellular communication, 5G network will face this challenge in future. However, there is few effective solutions to this problem for 5G network optimization. In this paper, a novel solution based on hot spot floating prediction is proposed. Our solution consists of a traffic prediction method for hot spot floating trend estimation, and a semi-dynamic distributed unit (DU) and active antenna unit (AAU) mapping to fit the forecasted high traffic burst with proper DU-AAU mapping. The proposed solution could fit real network irregular gNB distribution. Simulation outcomes indicate that the hot spot floating prediction precision outperforms around 10% in normalized root mean squired error with the existing prediction methods, and our semi-dynamic DU-AAU mapping solution receives a 20% throughput gain on average compared with that without DU-AAU mapping network solution.
{"title":"Rush Hour Capacity Enhancement in 5G Network Based on Hot Spot Floating Prediction","authors":"Shoufeng Wang, Fan Li, Hao Ni, Lexi Xu, Meifang Jing, Junyi Yu, Xidong Wang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00137","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00137","url":null,"abstract":"Rush hour network capacity enhancement is one of the most hard-to-solve problems in the field of network optimization. With the bust of data traffic requirement in cellular communication, 5G network will face this challenge in future. However, there is few effective solutions to this problem for 5G network optimization. In this paper, a novel solution based on hot spot floating prediction is proposed. Our solution consists of a traffic prediction method for hot spot floating trend estimation, and a semi-dynamic distributed unit (DU) and active antenna unit (AAU) mapping to fit the forecasted high traffic burst with proper DU-AAU mapping. The proposed solution could fit real network irregular gNB distribution. Simulation outcomes indicate that the hot spot floating prediction precision outperforms around 10% in normalized root mean squired error with the existing prediction methods, and our semi-dynamic DU-AAU mapping solution receives a 20% throughput gain on average compared with that without DU-AAU mapping network solution.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121325182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00037
Wenhan Zhan, H. Duan, Qingxin Zhu
By providing computation capability in the vicinity of vehicle terminals (VTs), multi-access edge computing (MEC) enables resource-demanding in-vehicle applications with significantly lower latency and less energy consumption. In this paper, we investigate the problem of offloading decision and resource allocation among multiple VTs to achieve the optimal system-wide user utility. Under the constraints of computation and wireless channel resources and VTs' mobility, this problem is mixed-integer non-linear programming (MINLP), which is generally NP-hard. A heuristic offloading decision method (HODM) is proposed, which decomposes the original problem into two subproblems, i.e., a convex computation allocation subproblem and a non-linear integer programming (NLIP) offloading decision subproblem, and settles them respectively. The convex subproblem is solved with a numerical method to obtain the optimal computation allocation among multiple offloading VTs, and a genetic algorithm (GA) based search algorithm is designed for the NLIP subproblem to determine the offloading decision. Several methods are utilized to reduce the enormous search space of this problem to make our solution more efficient. Extensive simulations are conducted by comparing with four baseline algorithms to demonstrate the superior performance of the proposed HODM.
{"title":"Multi-User Offloading and Resource Allocation for Vehicular Multi-Access Edge Computing","authors":"Wenhan Zhan, H. Duan, Qingxin Zhu","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00037","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00037","url":null,"abstract":"By providing computation capability in the vicinity of vehicle terminals (VTs), multi-access edge computing (MEC) enables resource-demanding in-vehicle applications with significantly lower latency and less energy consumption. In this paper, we investigate the problem of offloading decision and resource allocation among multiple VTs to achieve the optimal system-wide user utility. Under the constraints of computation and wireless channel resources and VTs' mobility, this problem is mixed-integer non-linear programming (MINLP), which is generally NP-hard. A heuristic offloading decision method (HODM) is proposed, which decomposes the original problem into two subproblems, i.e., a convex computation allocation subproblem and a non-linear integer programming (NLIP) offloading decision subproblem, and settles them respectively. The convex subproblem is solved with a numerical method to obtain the optimal computation allocation among multiple offloading VTs, and a genetic algorithm (GA) based search algorithm is designed for the NLIP subproblem to determine the offloading decision. Several methods are utilized to reduce the enormous search space of this problem to make our solution more efficient. Extensive simulations are conducted by comparing with four baseline algorithms to demonstrate the superior performance of the proposed HODM.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122055996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00139
Shiyu Zhou, Xiqing Liu, Yuanbing Tian, Bin Fu, Xiuyan Xia, Jin Ge
Based human visual speed perception characteristic, a video quanlity assessment(VQA) algorithm is introduced in the paper. Natural video statistics features extraction and weighting factors are incorporated in the scheme. In the VQA, considering the impact both video content itself and HVS's characteristic on human subjective perception, we propose weighting factors to scale the effect of those features, and it contains two parts: motion information and perception noise. And natural video statistics features relate to the spatial and temporal domain are extracted. The weighting factors would be used to combine both the temporal and spatial features, then generate the quality of each frame. Finally, the video quality score can be obtained by pooling scheme. LIVE database, EPFL-PoliMI database and some other generated test videos were used in our experiments, and the results indicate our model has outstanding performance.
{"title":"Blind Video Quality Assessment Based on Human Visual Characteristic","authors":"Shiyu Zhou, Xiqing Liu, Yuanbing Tian, Bin Fu, Xiuyan Xia, Jin Ge","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00139","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00139","url":null,"abstract":"Based human visual speed perception characteristic, a video quanlity assessment(VQA) algorithm is introduced in the paper. Natural video statistics features extraction and weighting factors are incorporated in the scheme. In the VQA, considering the impact both video content itself and HVS's characteristic on human subjective perception, we propose weighting factors to scale the effect of those features, and it contains two parts: motion information and perception noise. And natural video statistics features relate to the spatial and temporal domain are extracted. The weighting factors would be used to combine both the temporal and spatial features, then generate the quality of each frame. Finally, the video quality score can be obtained by pooling scheme. LIVE database, EPFL-PoliMI database and some other generated test videos were used in our experiments, and the results indicate our model has outstanding performance.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128493125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00151
Miaoqiong Wang, Kai Wei, Chunyu Jiang
This paper focuses on the processing requirements of time series data in industrial and IoT fields. The study of time series data processing in industry is continued for a long time, and a mature solution of using real-time/ historian database has been formed. However, with the new demand of Industrial Internet, old architectures are unable to fully support requirements (i.e., large amount and real-time analysis of industrial data). Meanwhile, a new architecture for processing real-time data in mobile Internet started to mature, this forms a solution called time-series database, which provides lots of new advantages. When we try to use a new technology to replace an old one, many aspects should be considered. This paper focuses on these challenges, starting with the demands of the industry, to analyze how to solve traditional problems with new technologies. This paper also analyzes the development trend of time series data processing and puts forward some general requirements for the application of new technology in the field of Industrial Internet, which lays a theoretical foundation for the application and development of basic technologies of Industrial Internet.
{"title":"Survey of Time Series Data Processing in Industrial Internet","authors":"Miaoqiong Wang, Kai Wei, Chunyu Jiang","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00151","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00151","url":null,"abstract":"This paper focuses on the processing requirements of time series data in industrial and IoT fields. The study of time series data processing in industry is continued for a long time, and a mature solution of using real-time/ historian database has been formed. However, with the new demand of Industrial Internet, old architectures are unable to fully support requirements (i.e., large amount and real-time analysis of industrial data). Meanwhile, a new architecture for processing real-time data in mobile Internet started to mature, this forms a solution called time-series database, which provides lots of new advantages. When we try to use a new technology to replace an old one, many aspects should be considered. This paper focuses on these challenges, starting with the demands of the industry, to analyze how to solve traditional problems with new technologies. This paper also analyzes the development trend of time series data processing and puts forward some general requirements for the application of new technology in the field of Industrial Internet, which lays a theoretical foundation for the application and development of basic technologies of Industrial Internet.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128681790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/iucc/dsci/smartcns.2019.00021
The workshop is aimed at discussing new advances in Energy-Efficient IoT. The workshop is addressed to IoT communication, trustworthiness in IoT, blockchain for IoT and energy-efficient protocols for sensor networks. The energy and trust issues among numerous agents are the bottlenecks in the development of IoT that need to be solved, and decentralized trusted mechanism is the tendency of development.
{"title":"Message from the EEIoT 2019 Workshop Chair","authors":"","doi":"10.1109/iucc/dsci/smartcns.2019.00021","DOIUrl":"https://doi.org/10.1109/iucc/dsci/smartcns.2019.00021","url":null,"abstract":"The workshop is aimed at discussing new advances in Energy-Efficient IoT. The workshop is addressed to IoT communication, trustworthiness in IoT, blockchain for IoT and energy-efficient protocols for sensor networks. The energy and trust issues among numerous agents are the bottlenecks in the development of IoT that need to be solved, and decentralized trusted mechanism is the tendency of development.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124588490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00078
Duo Zhai, Jing Shan, Jiaying Wang, Mingyang Shao, Jianzhao Cao
With the development of social network, current research on social network is analyzed by graph theory. According to the topology, studies can determine the social network, and analyze many practical problems, such as social ties, group cooperation, team influence, hot spread node of overlapping community and so on. Now, available research for community mining establishes algorithms widely by analyzing the section topology of neighbor vertexes. However, little consider topology formability or symmetries. For the research, we propose an algorithm, in which the complex graphs are considered as some isolated vertexes through the model of granular graph. This paper proposes an approach to mine outliers based on graph adjacency matrix and combinatorial mathematics, then analyses the symmetries of outliers for overall structure.
{"title":"Symmetry Structure Research of Complex Community from Disconnection Vertexes Perspective","authors":"Duo Zhai, Jing Shan, Jiaying Wang, Mingyang Shao, Jianzhao Cao","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00078","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00078","url":null,"abstract":"With the development of social network, current research on social network is analyzed by graph theory. According to the topology, studies can determine the social network, and analyze many practical problems, such as social ties, group cooperation, team influence, hot spread node of overlapping community and so on. Now, available research for community mining establishes algorithms widely by analyzing the section topology of neighbor vertexes. However, little consider topology formability or symmetries. For the research, we propose an algorithm, in which the complex graphs are considered as some isolated vertexes through the model of granular graph. This paper proposes an approach to mine outliers based on graph adjacency matrix and combinatorial mathematics, then analyses the symmetries of outliers for overall structure.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124171610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00072
Huang Jian, Yu Bai, Guiping Zhang, Wanwan Miu
Focusing on the research of sentence similarity calculation, this paper proposes a method combining bidirectional long short-term memory networks, attention mechanism and sememe (BILSTM-ATTENTION-SEMEME) to achieve better results on semantic representation and in-depth understanding of the semantic level, consequently better resolve the problem in the aspect of semantics in the field of intelligent customer service. This method first solves the semantic representation problem through a model based on bidirectional long short-term memory networks and attention mechanism (Bilstm-Attention), then combines the sememe information of HowNet in the training of word vectors to improve the performance of semantic under-standing. Experimental results show that the proposed method is effective in the computation of sentence similarity in the field of intelligent customer service, and it can well combine the sememe knowledge of HowNet with the deep learning model based on attention mechanism. Compared with the baseline system, the accuracy rate increased by 6.5%.
{"title":"Research on Sentence Similarity Calculation Based on Attention Mechanism and Sememe Information","authors":"Huang Jian, Yu Bai, Guiping Zhang, Wanwan Miu","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00072","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00072","url":null,"abstract":"Focusing on the research of sentence similarity calculation, this paper proposes a method combining bidirectional long short-term memory networks, attention mechanism and sememe (BILSTM-ATTENTION-SEMEME) to achieve better results on semantic representation and in-depth understanding of the semantic level, consequently better resolve the problem in the aspect of semantics in the field of intelligent customer service. This method first solves the semantic representation problem through a model based on bidirectional long short-term memory networks and attention mechanism (Bilstm-Attention), then combines the sememe information of HowNet in the training of word vectors to improve the performance of semantic under-standing. Experimental results show that the proposed method is effective in the computation of sentence similarity in the field of intelligent customer service, and it can well combine the sememe knowledge of HowNet with the deep learning model based on attention mechanism. Compared with the baseline system, the accuracy rate increased by 6.5%.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123593123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aiming at the problems of poor adaptability of the UAV during air combat and unreasonable decision-making mode, an optimal air combat decision-making method based on target trajectory prediction is proposed. Firstly, according to the non-empty air combat situation, different performance index functions are set, and then the target trajectory prediction is used to identify the enemy's intentions. According to the real-time situation analysis results, different performance index functions are selected to perform optimal control solution. Compared with other traditional methods, this method adopts the optimal control algorithm, and each maneuver made by the drone is optimal, which greatly improves the combat capability of the drone.
{"title":"UAV Attack and Defense Optimization Guidance Method Based on Target Trajectory Prediction","authors":"Guanglei Meng, Cheng Zhang, Shouye Liu, Runnan Zhao","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00108","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00108","url":null,"abstract":"Aiming at the problems of poor adaptability of the UAV during air combat and unreasonable decision-making mode, an optimal air combat decision-making method based on target trajectory prediction is proposed. Firstly, according to the non-empty air combat situation, different performance index functions are set, and then the target trajectory prediction is used to identify the enemy's intentions. According to the real-time situation analysis results, different performance index functions are selected to perform optimal control solution. Compared with other traditional methods, this method adopts the optimal control algorithm, and each maneuver made by the drone is optimal, which greatly improves the combat capability of the drone.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126341222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/iucc/dsci/smartcns.2019.00026
{"title":"DSCI 2019 Program Committee","authors":"","doi":"10.1109/iucc/dsci/smartcns.2019.00026","DOIUrl":"https://doi.org/10.1109/iucc/dsci/smartcns.2019.00026","url":null,"abstract":"","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128033344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/IUCC/DSCI/SmartCNS.2019.00035
Jiehong Wu, Xin Su
With the development of e-commerce, one of the essential ways of logistics distribution in the future is the distribution by UAVs. The limitations of the UAVs' resources and the distribution of express delivery need to be considered when delivery multiple merchandises. If the UAV task assignment is only based on the location of the delivery point, more UAVs are needed to accomplish the task. Therefore, it is necessary to divide the merchandises at the same distribution point. The goal of this paper is to use the minimum number of UAVs while minimizing the total distance traveled. This paper considers the two constraints of the maximum payload and cruising range of the UAV and models it according to these two constraints. Then the group-split-reorganize method is proposed to separate the packets that meet the constraints and optimize the intragroup path. Finally, experiments confirmed the feasibility and effectiveness of the method.
{"title":"UAV Task Assignment Algorithm Based on Splitting and Reorganization","authors":"Jiehong Wu, Xin Su","doi":"10.1109/IUCC/DSCI/SmartCNS.2019.00035","DOIUrl":"https://doi.org/10.1109/IUCC/DSCI/SmartCNS.2019.00035","url":null,"abstract":"With the development of e-commerce, one of the essential ways of logistics distribution in the future is the distribution by UAVs. The limitations of the UAVs' resources and the distribution of express delivery need to be considered when delivery multiple merchandises. If the UAV task assignment is only based on the location of the delivery point, more UAVs are needed to accomplish the task. Therefore, it is necessary to divide the merchandises at the same distribution point. The goal of this paper is to use the minimum number of UAVs while minimizing the total distance traveled. This paper considers the two constraints of the maximum payload and cruising range of the UAV and models it according to these two constraints. Then the group-split-reorganize method is proposed to separate the packets that meet the constraints and optimize the intragroup path. Finally, experiments confirmed the feasibility and effectiveness of the method.","PeriodicalId":410905,"journal":{"name":"2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125626191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS)
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